Numerical Methods and Optimization
Theory and Practice for Engineers
Series: Springer Optimization and Its Applications; 187;
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31 768 Ft
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Product details:
- Edition number 1st ed. 2021
- Publisher Springer
- Date of Publication 6 January 2023
- Number of Volumes 1 pieces, Book
- ISBN 9783030893682
- Binding Paperback
- No. of pages715 pages
- Size 235x155 mm
- Weight 1110 g
- Language English
- Illustrations 74 Illustrations, black & white; 154 Illustrations, color 477
Categories
Short description:
This text, covering a very large span of numerical methods and optimization, is primarily aimed at advanced undergraduate and graduate students. A background in calculus and linear algebra are the only mathematical requirements. The abundance of advanced methods and practical applications will be attractive to scientists and researchers working in different branches of engineering. The reader is progressively introduced to general numerical methods and optimization algorithms in each chapter. Examples accompany the various methods and guide the students to a better understanding of the applications. The user is often provided with the opportunity to verify their results with complex programming code. Each chapter ends with graduated exercises which furnish the student with new cases to study as well as ideas for exam/homework problems for the instructor. A set of programs made in Matlab? is available on the author?s personal website and presents both numerical and optimization methods.
MoreLong description:
This text, covering a very large span of numerical methods and optimization, is primarily aimed at advanced undergraduate and graduate students. A background in calculus and linear algebra are the only mathematical requirements. The abundance of advanced methods and practical applications will be attractive to scientists and researchers working in different branches of engineering. The reader is progressively introduced to general numerical methods and optimization algorithms in each chapter. Examples accompany the various methods and guide the students to a better understanding of the applications. The user is often provided with the opportunity to verify their results with complex programming code. Each chapter ends with graduated exercises which furnish the student with new cases to study as well as ideas for exam/homework problems for the instructor. A set of programs made in Matlab? is available on the author?s personal website and presents both numerical and optimization methods.
Table of Contents:
Preface.-Nomenclature.- 1. Interpolation and Approximation.- 2. Numerical Integration.- 3. Equation Solving by Iterative Methods.- 4. Numerical Operations on Matrices.- 5. Numerical Solution of Systems of Algebraic Equations.- 6. Numerical Integration of Ordinary Differential Equations.- 7. Numerical Integration of Partial Differential Equations.- 8. Analytical Methods for Optimization.- 9. Numerical Methods of Optimization.- 10. Linear Programming.- 11. Quadratic Programming and Nonlinear Optimization.- 12. Dynamic optimization.- Index.
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